data analysis n.
Skip this Video
Loading SlideShow in 5 Seconds..
Data analysis PowerPoint Presentation
Download Presentation
Data analysis

Loading in 2 Seconds...

play fullscreen
1 / 6

Data analysis - PowerPoint PPT Presentation

  • Uploaded on

Data analysis. As usual…. Copy your xxxxx_testing.psydat data file into the appropriate class_share folder for batch analysis Open your Excel data file and get the mean RT for consistent and conflicting conditions: Select the testing sheet (not training )

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

PowerPoint Slideshow about 'Data analysis' - emele

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
as usual
As usual…
  • Copy your xxxxx_testing.psydatdata file into the appropriate class_sharefolder for batch analysis
  • Open your Excel data file and get the mean RT for consistent and conflicting conditions:
  • Select the testing sheet (not training)
  • Work out your average scores for the conditions where the non-word was;
    • Pseudohomophone
    • Non-word but not a pseudohomophone
  • Were they different?
group analysis results
Group analysis results
  • This week we aren’t only interested in whether there was an effect of pseudohomophones
  • We also want to know if the effect was different for the groups A and B
  • For Group A the training involved (genuine) words that were actually homophones so according to Underwood’s theory these subjects were primed to words sounding similar
  • For Group B the training was simply words (not homophones) and non-words (also not pseudo-homophones)
so we want to know
So we want to know…
  • Did you all have a pseudohomophone effect? Two ways to think about this:
    • Compare your pseudohom RTs with control RTs

Test if RTpseudohom > RTcontrol

    • Or subtract your control from pseudohom RTs to create a ‘pseudohomophone effect’ size and compare that against zero

Effect = RTpseudohom - RTcontrol

Test if effect > 0

  • NB the two options above are actually identical mathematically
so we want to know1
So we want to know…
  • Did the homophone training have an effect?
    • Use option 2 from previous slide, and compare the strength of the pseudo-homophone effect (the difference score) between the two conditions

EffectgpA= RTpseudohom- RTcontrol

EffectgpB= RTpseudohom- RTcontrol

Test if EffectgpA > EffectgpB

for your report
For your report
  • You’re testing two hypotheses here:
    • Do people show a pseudohomophone effect in the new procedure?
    • Does it depend on training words?
  • For the first hypothesis the DV is reaction time
  • For the second hypothesis the DV is the strength of pseudohomophone effect
  • Before leaving make sure you have all the experiment information you’ll need to write your report